OFAR: A Multimodal Evidence Retrieval Framework for Illegal Live-streaming Identification

no code implementations • 25 Apr 2023 • Lin Dengtian, Ma Yang, Li Yuhong, Song Xuemeng, Wu Jianlong, Nie Liqiang

OFAR consists of three modules: Query Encoder, Document Encoder, and MaxSim-based Contrastive Late Intersection.

Contrastive Learning Retrieval

GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback

1 code implementation • 3 Nov 2021 • Wei Yinwei, Wang Xiang, Nie Liqiang, He Xiangnan, Chua Tat-Seng

Reorganizing implicit feedback of users as a user-item interaction graph facilitates the applications of graph convolutional networks (GCNs) in recommendation tasks.

Multimedia recommendation

Hierarchical User Intent Graph Network forMultimedia Recommendation

1 code implementation • 28 Oct 2021 • Wei Yinwei, Wang Xiang, He Xiangnan, Nie Liqiang, Rui Yong, Chua Tat-Seng

In this work, we aim to learn multi-level user intents from the co-interacted patterns of items, so as to obtain high-quality representations of users and items and further enhance the recommendation performance.

Attentive Long Short-Term Preference Modeling for Personalized Product Search

1 code implementation • 26 Nov 2018 • Guo Yangyang, Cheng Zhiyong, Nie Liqiang, Wang Yinglong, Ma Jun, Kankanhalli Mohan

Our model adopts the neural networks approach to learn and integrate the long- and short-term user preferences with the current query for the personalized product search.